2 citations · 3 across the 5 of their papers we have counts for
5 papers
Palermo: Improving the Performance of Oblivious Memory using Protocol-Hardware Co-Design
Haojie Ye, Yuchen Xia, Yuhan Chen +6
Oblivious RAM (ORAM) hides the memory access patterns, enhancing data privacy by preventing attackers from discovering sensitive information based on the sequence of memory accesse…
Understanding the Performance and Estimating the Cost of LLM Fine-Tuning
Yuchen Xia, Jiho Kim, Yuhan Chen +4
Due to the cost-prohibitive nature of training Large Language Models (LLMs), fine-tuning has emerged as an attractive alternative for specializing LLMs for specific tasks using lim…
Everest: GPU-Accelerated System For Mining Temporal Motifs
Yichao Yuan, Haojie Ye, Sanketh Vedula +2
Temporal motif mining is the task of finding the occurrences of subgraph patterns within a large input temporal graph that obey the specified structural and temporal constraints. D…
Vector-Processing for Mobile Devices: Benchmark and Analysis
Alireza Khadem, Daichi Fujiki, Nishil Talati +2
Vector processing has become commonplace in today's CPU microarchitectures. Vector instructions improve performance and energy which is crucial for resource-constraint mobile devic…
Accelerating Graph Analytics on a Reconfigurable Architecture with a Data-Indirect Prefetcher
Yichen Yang, Jingtao Li, Nishil Talati +5
The irregular nature of memory accesses of graph workloads makes their performance poor on modern computing platforms. On manycore reconfigurable architectures (MRAs), in particula…